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Scala Functional Programming Patterns

You're reading from   Scala Functional Programming Patterns Grok and perform effective functional programming in Scala

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Product type Paperback
Published in Dec 2015
Publisher
ISBN-13 9781783985845
Length 298 pages
Edition 1st Edition
Languages
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Author (1):
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Atul S. Khot Atul S. Khot
Author Profile Icon Atul S. Khot
Atul S. Khot
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Toc

Table of Contents (13) Chapters Close

Preface 1. Grokking the Functional Way 2. Singletons, Factories, and Builders FREE CHAPTER 3. Recursion and Chasing your Own Tail 4. Lazy Sequences – Being Lazy, Being Good 5. Taming Multiple Inheritance with Traits 6. Currying Favors with Your Code 7. Of Visitors and Chains of Responsibilities 8. Traversals – Mapping/Filtering/Folding/Reducing 9. Higher Order Functions 10. Actors and Message Passing 11. It's a Paradigm Shift Index

Tail recursion to the rescue


There is a technique, an optimization really, that helps us get out of the logjam. However, we need to tweak the code a bit for this. We will make the recursive call as the last and only call. This means that there is no intermediate context to remember. This last and only call is called the tail call. Code in this tail call form is amenable to TCO. Scala generates code that, behind the scenes, uses a loop—the generated code does not use any stack frames:

import 
scala.annotation.tailrec

def count(list: List[Int]): Int = {
  @tailrec   // 1
  def countIt(l: List[Int], acc: Int): Int = l match 
{
  
  case Nil => acc // 2
    case head :: tail => countIt(tail, acc+1) // 3 
  }
  countIt(list, 0)
}

The changes are like this:

We have a nested workhorse method that is doing all the hard work. The count method calls the countIt nested recursive method, with the list it got in the argument, and an accumulator. The earlier intermediate context is now expressed...

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